Wednesday, August 28, 2013

I spend a lot of time bashing epidemiological papers, because they are such easy targets and get such breathless headlines. I am pleased to have the opportunity to bash an economics paper, courtesy of a tip from esteemed colleague David Figlio. David pointed me to a paper that concludes that more sex produces higher wages. It's forthcoming in the International Journal of Manpower (no, I am not making this up).

When we compare the sexual activity of those with high and low wages, we might worry that there are confounding factors that lead a person to succeed in both the mating market and labor market. For example, if you are persuasive enough to talk someone out of their pants, you may well be persuasive at talking yourself into a raise. If you have the health and energy to be productive at work, those traits help you be more reproductive, too. Simultaneity bias is also plausible: the relationship could run the other way, with higher wages leading to more success in the sex market.

If we wanted to apply gold-standard research methods to this question, we would gather up volunteers, randomize them into treatment and control groups, and expose members of the the treatment group to an intervention that increases their sexual activity. I will leave this intervention to your imagination. We would then compare the wages of the treatment and control group to get the effect of the intervention. A bit more statistical fiddling would get us the causal impact on sex on wages, at least for those who were stimulated to action by the intervention.

In this paper, the author does not run a randomized trial, but instead uses observational data to draw his conclusions - specifically, an instrumental-variables strategy. The idea here is to find a variable (the "instrument") that is correlated with the "treatment" of interest (sex) but is correlated with the outcome (wages) onlythroughthat treatment.In this particular context, an instrument is valid if it 1) is correlated with sexual activity and 2) is not correlated with wages through any channel except sexual activity. The first condition is called the relevance condition and the second the exclusion restriction.

The relevance condition is testable. A strong instrument (must ... resist... salacious ... pun) scores an F-test of 10 or above in the equation that estimates the relationship between sex and the instrument. Instruments that pass this test are a dime a dozen. Don't let a strong instrument turn your head - hold out for a plausible exclusion restriction. The exclusion restriction is not formally testable - it's an identifying assumption. A good instrumental-variable paper will kick the tires hard on the instrument, using both data and knowledge of the world to make the case that there is no possible channel through which the instrument affects the outcome of interest.

In this paper, the author's identifying assumption is that religiosity has no relationship with economic activity except through its (negative) correlation with sexual activity.

Could religion have a relationship with wages, other than through its "effect" on sex? Are these results believable?

"In a study of more than 40,000 individuals, researchers found that people who drink more than 28 cups per week (that's about four a day) have a 21 percent increased mortality risk and a more than 50 percent increased risk if under 55."

Kudos to the reporter for helpfully dividing 28 by 7 for the reader! I might have severely misinterpreted this research otherwise.

Now, how about we give the magnitudes of our estimates a sniff test before publishing? Four cups of coffee a day increases mortality by 50%? This is enormous. Note that this is an increase in mortality from all causes - not just mortality from conditions that might have a plausible, theoretical link to coffee consumption, such as bladder cancer, uncontrolled tremors, and concussion from bouncing off walls. Here is a sniff test of the magnitude of this estimate: a similar, correlational analysis showed that light smoking (less than half a pack of day) is associated with an increase in all-cause mortality of 30%. Heavy smoking (more than half a pack a day), an increase of 80%. These magnitudes are in the same ballpark as the coffee study, which immediately suggests to me that the coffee estimates are absurd. I would hazard that maybe, just maybe, there are confounding factors that the coffee study did not pick up. For example, the authors did not control for physical activity, education or marital status. If inactive, single, high school dropouts drink more coffee, we would get the inflated estimates we see in this paper, since this population dies younger than those who are active, married and better educated.

Now, the smoking estimates have the same weakness as the coffee estimates: they are conditional correlations that do not imply cause and effect. The critical difference is that in the case of cigarettes we have plausible theoretical links between exposure and mortality (lung cancer, emphysema) and decades of clinical and lab science that shows convincingly that cigarettes kill people. Coffee? Nada, though the bluestockings have been trying for a long time to show that it must be harmful. With this lack of theory and evidence linking coffee and mortality, the coffee researchers should be especially cautious in interpreting their correlations as causal.

So, file this one under lousy research as well as lousy reporting. This study gives the cocoa case a run for its money. We are fast building a hall of shame of hot-beverage research and reporting.

Tuesday, August 13, 2013

In today's headlines, a story about autism that communicates science so much better than was the case in the cocoa debacle. This is a wonderful example of how reporters and researchers can communicate research in accurate yet non-technical language. Reporters, researchers and press offices, take note!

First, the headline: "Preliminary study suggests link between inducing labor and autism." The wording does an excellent job of communicating that this is suggestive work. The headline appropriately makes no health recommendations, which would not be justified by this research.

Second, the reporting: "A new study suggests that babies born after their mother's labor is medically induced or accelerated might have an increased risk of autism. The study, published today in theacademic journal JAMA Pediatricsis preliminary and does not prove cause and effect." Be still, my heart. Perfect.

Third, the researcher's quotes: "Still, it’s a statistical signpost directing researchers to take a closer look at possible links between expediting labor — often it’s to save the life of the mother and child — and autism, said Marie Lynn Miranda, lead author of the paper and a University of Michigan professor of pediatrics and environmental informatics. 'We have a lot of kids with autism and we know the rates are increasing, but we don’t the causes,' she said." Professor Miranda describes the process of science beautifully. She found an association - a statistical signpost - that has produced a testable hypothesis that scientists can pursue with methods that can extract a causal relationship.

Monday, August 12, 2013

I have a new paper with my Cambridge collaborators on the effects of Boston's charter schools on preparation for college and college choice. In previous work (which I blogged about here), we looked at the effects of these schools on the state's standardized test, the MCAS. We found large and positive effects of charter attendance, with effects largest for kids who most need help: Blacks, Hispanics, those with limited English proficiency, special ed kids, those who have the lowest baseline scores. The effect sizes are huge - kids at charters gain 0.1-0.2 standard deviations each year on their peers at the traditional public schools. This earlier paper on test scores has now been published in the Quarterly Journal of Economics.

Test scores are not what makes the world go round, however - the aim of education is to make better, smarter, happier, well-rounded citizens. While we don't measure all of these things in our new work, we gain some ground by examining preparation for college (in the form of the SAT and Advanced Placement scores), college entry and choice of college. As the children attending these schools age, we hope to look at yet more outcomes.

Summary of the paper's findings:

We use admissions lotteries to estimate the effects of attendance at Boston's charter high schools on college preparation, college attendance, and college choice. Charter attendance increases pass rates on the high-stakes exam required for high school graduation in Massachusetts, with especially large effects on the likelihood of qualifying for a state-sponsored college scholarship. Charter attendance has little effect on the likelihood of taking the SAT, but shifts the distribution of scores rightward, moving students into higher quartiles of the state SAT score distribution. Boston's charter high schools also increase the likelihood of taking an Advanced Placement (AP) exam, the number of AP exams taken, and scores on AP Calculus tests.

Finally, charter attendance induces a substantial shift from two- to four-year institutions, though the effect on overall college enrollment is modest. The increase in four-year enrollment is concentrated among four-year public institutions in Massachusetts. The large gains generated by Boston's charter high schools are unlikely to be generated by changes in peer composition or other peer effects.

The numbers behind this summary are pretty impressive. Charter attendance increases SAT scores by about a third of a standard deviation and doubles the likelihood of taking and passing an Advanced Placement test. Charter attendance quadruples the likelihood of taking the AP calculus exam (from 6% to 27%) and quintuples the likelihood of getting a passing score (from 1.5% to 9%). As these numbers make clear, a lot of the kids induced to take an AP course don't end up getting college credit for it. The fact that they are able to take the class at all, however, indicates that they have taken a strong set of college-prep classes. In particular, you can't take calculus without having taken algebra, trigonometry and geometry - all of which you need to be in the running for a selective, four-year college and a STEM career.

Charter attendance also affects postsecondary outcomes. Most strikingly, kids who attend Boston's charters are 17 percentage points more likely than their comparable peers to attend a four-year college. There also appears to be a positive effect on attending any college at all, but these estimates are not precise enough to take to the bank. We have to wait for more cohorts of these kids to age into college before we can say anything definitive on this point.

I discussed why we use admissions lotteries to get at these results in my earlier post. To recap: the key empirical challenge in understanding the effect of charter schools is selection bias: kids who go to charter schools are different in both observable and unobservable ways from kids who don't. Are kids whose parents are highly educated or motivated concentrated at charters? Kids whose test scores were plummeting in the public schools? Kids who were not challenged in the public schools? All of these differences would contaminate any effort to compare the achievement of kids at charters and kids at public schools.

We solve this problem by exploiting the randomized lotteries conducted by over-subscribed charter schools. The lottery approach focuses on students who apply to charters, comparing outcomes for those who lose the lottery to those who win. A mere coin flip (or randomly-generated number) separates the lottery winners and losers, so we can be confident that they are alike in every observable and unobservable way - except for their charter school attendance. This closely approximates the gold standard of a randomized, controlled trial. The What Works Clearinghouse has reviewed an earlier version of our paper and given it a provisional "Meets Standards without Reservation."

Thursday, August 8, 2013

"A study of 60 elderly people with no dementia found two cups of cocoa a day improved blood flow to the brain in those who had problems to start with."

There was no randomized control group in this study, nor even a non-randomized control group. It has a pre-post design:

"[R]esearchers asked 60 people with an average age of 73 to drink two cups of cocoa a day - one group given high-flavanol cocoa and another a low-flavanol cocoa - and consume no other chocolate."

Time passed, lives were lived, and people drank cocoa. Then, the researchers attributed changes to the drinking of cocoa:

"Study author Dr. Farzaneh Sorond, a neurologist at Brigham and Women's Hospital and assistant professor of neurology at Harvard Medical School, said chocolate seemed to boost the brain's blood supply, citing an 8.3 percent increase in blood flow after a month's worth of hot cocoa...'In people with impaired blood flow, she added, "cocoa may be beneficial by delivering more fuel.'"

This research design is not up to the inferences and recommendations being made. It is a flimsy foundation for any medical advice. Yet that is how it is being sold: "Chocolate is the New Brain Food, "Cocoa Can Prevent Memory Loss."

Crappy science reporting is often the dangerous offspring of a press office that writes a sexy, misleading press release and lazy reporters who swallow it whole. A researcher can lose control of the message. The quotes above indicate that, in this case, the researcher is also complicit.